C&ENVENG 7114 - Advanced Hydrological Modelling & Water Resource Management

North Terrace Campus - Winter - 2018

The course will cover advanced techniques for hydrological modelling, including stochastic modelling of rainfall and runoff processes and catchment modelling of hydrological processes. The stochastic modelling component will focus on single and multi-site time series models for rainfall and/or runoff. The catchment modelling component will include the development and application of lumped through to semi-distributed/distributed approaches. For both components, students will develop their skills on model development, calibration and evaluation. A focus of the course will be the use of Bayesian approaches for model calibration and prediction, including techniques for estimating the various sources of predictive uncertainty. These techniques will be applied in water resource management context, utilising case studies from drought/flood risk assessment and hydrological forecasting to illustrate the practical value of the approaches.

  • General Course Information
    Course Details
    Course Code C&ENVENG 7114
    Course Advanced Hydrological Modelling & Water Resource Management
    Coordinating Unit School of Civil, Environmental & Mining Eng
    Term Winter
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 39 hours per week (based on four weeks of intensive study)
    Available for Study Abroad and Exchange N
    Prerequisites C&ENVENG 3077
    Restrictions BE (Civil & Struct), BE (Civil & Env), ME (Civil & Struct) and ME (Civil & Env) students only.
    Course Description The course will cover advanced techniques for hydrological modelling, including stochastic modelling of rainfall and runoff processes and catchment modelling of hydrological processes. The stochastic modelling component will focus on single and multi-site time series models for rainfall and/or runoff. The catchment modelling component will include the development and application of lumped through to semi-distributed/distributed approaches. For both components, students will develop their skills on model development, calibration and evaluation. A focus of the course will be the use of Bayesian approaches for model calibration and prediction, including techniques for estimating the various sources of predictive uncertainty. These techniques will be applied in water resource management context, utilising case studies from drought/flood risk assessment and hydrological forecasting to illustrate the practical value of the approaches.
    Course Staff

    Course Coordinator: Professor Dmitri Kavetski

    Course Co-ordinator: Assoc. Prof. Mark Thyer
    Engineering North, N107a
    Phone: +61 8 8313 0770
    e-mail: mark.thyer@adelaide.edu.au
    Profile: http://researchers.adelaide.edu.au/profile/mark.thyer

    Lecturer: Prof. Dmitri Kavetski
    Engineering North, N153
    Phone: +61 8 8313 1710
    e-mail: dmitri.kavetski@adelaide.edu.au
    Profile: http://www.adelaide.edu.au/directory/dmitri.kavetski

    Information on office hours and other course staff (tutors etc) will be made available via MyUni course


    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

     
    1 Knowledge of advanced stochastic models (lag-one autoregressive, single and multi-site approaches, hidden Markov models, Bayesian hierarchical methods, transformations) for range of hydrological applications
    2 Knowledge and application of the principles of model development, calibration and evaluation approaches in the context of stochastic hydrological models
    3 Knowledge, application and evaluation of a range of model calibration approaches, including method of moments, maximum likelihood, and Bayesian approaches
    4 Creation and application of stochastic hydrological models using the R software package and assessment of its impact on drought risk assessment
    5 Knoweldge and application of advanced programming practises in the context of hydrological modelling
    6 Knowledge of the general principles underlying hydrological models, including similarities and differences between conceptual vs physical models, and between lumped vs distributed models
    7 Application of mass balance and constitutive functions, explicit and implicit time stepping approximations to derive, solve and implement a lumped conceptual model
    8 Knowledge of the principles of calibration, including similarities and differences between manual vs optimization-based calibration vs Bayesian/statistical inference, including Monte Carlo techniques, such as Markov Chain Monte Carlo
    9 Application of least squares techniques to implement parameter calibration and probabilistic prediction for a simple reservoir model

     
    The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
    The course is designed to develop the following Elements of Competency: 1.1   1.2   1.3   1.4   2.1   2.2   2.3   3.2   3.3   3.4   3.5   

    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1-9
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    2-9
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    2-9
  • Learning Resources
    Required Resources
    Lecture Slides
    The lecture slides will form part of the notes for this course. They will be made available on course MyUni site.

    Course Information
    The course information document is a required resource. It will be made available from the course MyUni site. .
    Recommended Resources
    Design Project Information and Resources:
    Relevant information, data and software required to complete the design project(s) are in the relevant sections of the MyUni site.

    Relevant References
    Relevant references, including journal papers and texts will be made available in the relevant sections of the MyUni site.
    Online Learning
    Students will be required to have a basic understanding of the software package, R to complete this course.
    Students will be provided with self-paced, interactive, online learning module to help develop their skills in R
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course consists of a set of integrated activities (lectures, tutorials and design project sessions) designed to provide you with the opportunity to achieve the course learning objectives in a supportive and motivating context.


    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Contact Hours Private Study Hours Total
    Lectures 26 0 26
    Tutorials 18 27 45
    Design (Phase 1) 8 24 (per person) 32
    Design (Phase 2) 8 24 (per person) 32
    Exam Preparation 0 18 18
    Exam 3 0 3
    Total 63 93 156
    Learning Activities Summary
    The centrepiece of the course is a two different design projects in each part the course. You will learn the fundamental principles / underlying theory required to complete the project as part of a number of learning cycles consisting of a series of lectures and tutorials. The lectures will introduce the theory and the tutorials will provide with straightforward applications of the theory. The Design Project provides you with the opportunity to gain an in-depth understanding of the material covered by applying it in a realistic context.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    Due (week)*
    Hurdle criteria Learning outcomes
    Online Quizzess 1 Individual Formative/Summative Week 2 1.2.3
    Design Project Phase 1 24 Group Formative / Summative Week 3 1. 2. 3. 4. 5.
    Design Project Phase 2 25 Group Formative / Summative Week 5 5. 6. 7. 8. 9.
    Exam 50 Individual Summative min. 40% 1. 2. 3. 6. 7. 8.
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
     
    This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s): 1. a. i    1. c.   
     
    This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.
    Assessment Related Requirements
    Groupwork:
    This course includes assessment tasks undertaken within groups (usually pairs). These groups are self-selected. The same mark will be allocated to all group members and will be based on group output only. Group processes are not assessed explicitly in this course. To maintain the integrity of the assessment task(s) there is a requirement that all students within a group contribute to each assessment activity. Where there is evidence that group members have not sufficiently contributed to a group assessment task, the Academic Honesty policy may be applied. 

    Hurdles:
    In order to pass this course, students must obtain at least 40% for the exam. Where the exam hurdle is not met students will receive a course result of the lesser of their calculated grade and the nominal grade of 45, Fail. An additional assessment exam will be available to eligible students. Students should refer to the Modified arrangements for coursework assessment policy for eligibility criteria.
    Assessment Detail
    Details about the assessment tasks, including due dates and assessment criteria will be made available on the MyUni site for the course.
    Submission
    The submisson time for all assessment tasks is 4pm on the due date, unless otherwise specified.

    All written submissions should be submitted online via the Assessment section of the MyUni course site.

    Late submissions will only be accepted for the Design Project. However, there will be a loss of 10% of the marks obtained if the submission is less than 24 hours late, 20% if the submission is between 24 and 48 hours late and so on. Extensions will only be granted in special circumstances (e.g. illness) and must be sought for each assessment task individually. Extensions will not be granted less than 24 hours before the deadline for a given task, with the exception of a medical certificate.

    Submissions should follow the guidelines as provided on MyUni.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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